Michael J. Clark

General Statement

I do a lot of statistical programming, and combined with my consulting experience, this means I’ve covered a lot of ground- statistically, in terms of dealing with many types of data both big and small, and with ideas, just burgeoning or traipsing well established domains. Clients come from a wide variety of backgrounds and the range of their needs is quite extensive. In a given week, I might help someone with some code to scrape the web to obtain their data in an efficient fashion, employ a Bayesian model to incorporate spatial random effects, use machine learning techniques to predict rare events, develop theoretical motivations to eventually be tested with structural equation modeling, or maybe help an undergrad understand some regression basics. Among my own work, clarity, especially via visualization, as well as reproducibility, are the goals I continually strive for. Underlying all of my efforts is a willingness to use whatever means necessary to gain more knowledge about the underlying mechanisms that produce the information (in the form of data) we seek to understand better, and a view of science as software development, continually upgraded, and never static.

Skills

Programming

I primarily work within the R statistical environment for most of my own needs, including the development of my own packages, and I have years of experience with it. I use Stan for Bayesian analysis, and Python for things such as web scraping, text analysis, machine learning, and deep learning. I have experience utilizing a high performance computing environment and parallel processing in general.

I develop R packages primarily for personal use or for fun, but I also use them to improve my coding skills by adhering to common coding standards, striving for high code coverage, engaging in unit testing. All would pass CRAN checks as well. These include: visibly, noiris , tidyext, gammit, lazerhawk, 198R, five38clubrankings.

In addition to these, though they are not publicly available, I’ve created even more involved packages for specific project work.

Analysis

On the analytical side, aside from traditional methods with generalized linear models, mixed models, and latent variable models, I’ve also extended those approaches to the Bayesian world and expanded upon them there. I’ve examined nonlinear relationships via additive models, gaussian processes, etc. I’ve analyzed different types of networks and graphical models generally. I have explored time and space issues via mixed/multilevel/growth model frameworks, survival analysis, and spatial models for both the discrete and continuous setting. I’ve also utilized various machine learning approaches in a variety of settings. I’ve also dealt with unstructured data situations such as that found in the analysis of text.

Workshops

Data Science Skills Series	Traditional Workshops
More Mixed Models	Introduction to Machine Learning
Generalized Additive Models	Mixed Models with R
Patchwork and gganimate	Structural Equation Modeling
Easy Bayes with rstanarm and brms	Introduction to Regression
Visualization in R
Programming in R
Data Processing in R
Introduction to RMarkdown
Text Analysis with R
Generalized Additive Models
Become a Bayesian in 10 minutes
Engaging the Web with R
Getting More from RStudio
Ceci n’est pas une %>%

Professional Experience

Statistician Lead

CSCAR, University of Michigan

Since 2015, I’ve held a position providing statistical consultation for faculty and students from various disciplines across campus, as well as serving as analytical lead or providing consulting services for specific research projects. I also conduct workshops related to statistical programming and modeling techniques.

Statistical Consultant

CSSR, University of Notre Dame

Previously, I held a position providing aid at any stage of various research projects for students, staff and faculty from various departments on campus, particularly, but not exclusive to, those of the Social Sciences.

Other

Lecturer, Teaching fellow, Research assistant, Test center administrator, Book department clerk, Assistant at a behavioral health care center, Phone survey conductor, Stablehand, Pizza delivery driver and cook, Odd jobs via temporary agency, General retail.

Education

Ph.D. Experimental Psychology, Concentration: Statistics UNT

B.Sc. Philosophy & Psychology, Cum Laude, TCU

Dissemination of Research

Representative

George, B. et al. (2017). Readiness of US General Surgery Residents for Independent Practice. Annals of Surgery. (link to article; 99th Altmetric percentile).

Archie, E.A., Tung, J., Clark, M., Altmann, J., Alberts, S.C. (2014). Social affiliation matters: both same-sex and opposite-sex relationships predict survival in wild female baboons. Proceedings of the Royal Society: of London Series B. (link to article; 99th Altmetric percentile).

Recent

Scully, et al. (under revision). Concordance between expert and non-expert ratings of condensed video-based trainee operative performance assessment. Journal of Surgical Education.

Dabney, B., Kalisch, B., and Clark, M. (under revision). A Revised MISSCARE Survey: Results from Initial Pilot Testing. Applied Nursing Research.

Schuler, B. R., et al. (submitted). Poverty and Food Insecurity Predict Mealtime Structure: Mediating Pathways of Parenting Style and Depressive Symptoms. Journal of Child and Family Studies.

King, C. et al. (in preparation). LET’s CONNECT Community Mentorship Program for Adolescents with Peer Social Problems and Risk for Suicidal Behavior: A Randomized Intervention Trial.

George, B. C., Clark, M., et al. (in preparation) The Gap Between Resident and Faculty Perceptions of Resident Performance in the OR: a Multi-Center Trial.

Abbot, K, Chen, X., Clark, M. et al. (2019). Number of operative performance ratings needed to reliably assess the difficulty of surgical procedures. Journal of Surgical Education.

Ahle, S. L., Schuller, M., Clark, M. J., et al. (2019) Do End-of-Rotation Evaluations Adequately Assess Readiness to Operate? Academic Medicine.

King, C. et al. (2018). Let’s Connect Community Mentorship Program for Youth with Peer Social Problems: Preliminary Findings from a Randomized Effectiveness Trial. Journal of Community Psychology.

Arango, A., et al. (2018). The Protective Role of Connectedness on Depression and Suicidal Ideation among Bully Victimized Youth. Journal of Clinical Child and Adolescent Psychology.